-40- 
of each are summarised in Table 1. Scans 1-4, 13-16 and 16-20 
were captured with high accuracy and last pulse (standard 
parameters) but different resolutions. Four data sets were 
captured at each resolution to gauge repeatability, though only 
one ultra resolution scan could be captured with available 
battery power. For scans 5-8 and 9-12, the pulse mode and 
accuracy parameters were respectively changed. 
Scan Numbers 
Resolution 
Accuracy 
Pulse 
1-4 
Coarse 
High 
Last 
5-8 
Coarse 
High 
First 
9-12 
Coarse 
Standard 
Last 
13-16 
Medium 
High 
Last 
17-20 
Fine 
High 
Last 
21 
Ultra 
High 
Last 
Table 1. Scanner Performance Test Cases. 
Figure 1. Histogram of Plane Fit Residuals 
(Individual Coarse Resolution, High-Accuracy Scan) 
2.3 Experimental Results 
Resulting from the testing was a large data set from which 
reliable precision estimates could be obtained. In total, nearly 
2.1 million individual point measurements were captured. For 
each of the 336 (16 x 21) individual scans and the 21 combined 
(i.e. mean of 16) scans, a least-squares plane estimate was 
removed from the data and statistics compiled from the 
residuals. The mean scan was calculated by averaging the 16 
sets of co-ordinates for each point. Some of the findings from 
these data are presented below. 
2.3.1 Individual vs. Mean Scans. For each case, the statistics 
of the 16 individual and average (mean) plane fits were 
compared. For all high accuracy mode data sets individual scan 
precision was ±20-22 mm, while for the mean scan the 
precision was ±5-6 mm. Clearly, these follow the basic “one 
over the square root of n” rule from statistics. In a more 
practical context, this result indicates that a scanner with 
seemingly coarse rangefinder precision can yield more precise 
measurements through the exploitation of statistics. 
2.3.2 Precision vs. Sampling Resolution. Precision was found 
to be independent of sampling resolution. Though not 
unexpected, this result indicates that one need not necessarily 
acquire an ultra resolution scan in order to attain a desired level 
of precision. 
2.3.3 Precision vs. Pulse Mode Choice. No significant 
differences in precision were detected between the first-pulse 
and last-pulse data sets. However, it is acknowledged that a 
relatively small portion of a wall was imaged at normal 
incidence. A more complex shape oriented obliquely may 
produce different results. This is the subject of ongoing testing. 
2.3.4 Precision vs. Measurement Accuracy Mode. Operation 
of the scanner in standard accuracy mode permits measurement 
of longer ranges (up to 700 m), which is clearly an 
advantageous feature for larger-scale projects or where site 
access is restricted. However, the longer range comes at the 
cost of lower precision. From four standard accuracy data sets, 
individual scan precision was estimated to be ±35-38 mm, while 
precision for the mean scans was ±9 mm in all four cases. 
Clearly there is a degradation of precision, but in this case only 
by about a factor of 1.7 instead of the expected factor of 2 
quoted by the vendor. 
Figure 1 is a histogram of plane fit residuals from an individual 
coarse resolution, high accuracy scan. Figure 2 is a histogram 
of residuals for an individual coarse resolution, standard 
accuracy scan. The sample size of each was 999 points and 
both scans were acquired in last pulse mode. As might be 
expected, the high accuracy scan histogram follows a Gaussian 
shape. This behaviour was observed for all high accuracy 
scans, regardless of resolution or pulse mode choice. Analysis 
of the standard accuracy histogram reveals a greater dispersion 
and a possible bias indicated by the minor lobe at 0.05 m. 
Figure 2 is representative of the other standard accuracy scans. 
Whatever the mechanism used for deriving longer-range 
measurements, it is clearly biased. 
100 
90 
80 
Figure 2. Histogram of Plane Fit Residuals 
(Individual Coarse Resolution, Standard-Accuracy Scan) 
3. SENSITIVITY TESTING 
3.1 Description 
As will be described in Section 4, the scanner’s ability to sense 
deformation was tested on a real load-testing project. 
Laboratory simulations were also conducted to quantify scanner 
sensitivity in a controlled environment. The assessment was 
performed by analysing differences in surfaces modelled from 
laser scanner data rather than on a point-wise basis, as is 
commonplace in photogrammetric monitoring campaigns.